chore: import upstream snapshot with attribution

tools/tensorflow-quantization/examples/efficientnet/export.py

@@ -0,0 +1,59 @@
+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+
+import tensorflow as tf
+import argparse
+from utils import create_efficientnet_model
+from tensorflow_quantization.quantize import quantize_model
+from tensorflow_quantization.custom_qdq_cases import EfficientNetQDQCase
+
+
+def export_saved_model(model_version="b0"):
+    model = create_efficientnet_model(model_version=model_version)
+    q_model = quantize_model(model, custom_qdq_cases=[EfficientNetQDQCase()])
+    if args.ckpt:
+        q_model.load_weights(args.ckpt).expect_partial()
+
+    tf.keras.models.save_model(q_model, args.output)
+    print("Exported the model to {}".format(args.output))
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Export saved model for efficientnet_b0"
+    )
+    parser.add_argument(
+        "--ckpt",
+        type=str,
+        default="qat/checkpoints_best",
+        help="Path to pretrained QAT efficientnet checkpoint.",
+    )
+    parser.add_argument(
+        "--output",
+        type=str,
+        default="qat/saved_model",
+        help="Path to pretrained QAT saved model.",
+    )
+    parser.add_argument(
+        "--model_version",
+        type=str,
+        default="b0",
+        help="EfficientNet model version, currently supports {'b0', 'b3'}.",
+    )
+    args = parser.parse_args()
+    export_saved_model(args.model_version)